Computational Methods for Estimating the Kinetic Parameters of Biological Systems
| 企业作者: | |
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| 其他作者: | |
| 总结: | XI, 379 p. 105 illus., 96 illus. in color. text |
| 语言: | 英语 |
| 出版: |
New York, NY :
Springer US : Imprint: Humana,
2022.
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| 版: | 1st ed. 2022. |
| 丛编: | Methods in Molecular Biology,
2385 |
| 主题: | |
| 在线阅读: | https://doi.org/10.1007/978-1-0716-1767-0 |
| 格式: | 电子 电子书 |
书本目录:
- Current Approaches of Building Mechanistic Pharmacodynamic Drug-Target Binding Models
- An Extended Model Including Target Turnover, Ligand-Target Complex Kinetics, and Binding Properties to Describe Drug-Receptor Interactions
- Beyond the Michaelis-Menten: Bayesian Inference for Enzyme Kinetic Analysis
- Multi-Objective Optimization Tuning Framework for Kinetic Parameter Selection and Estimation
- Relationship between Dimensionality and Convergence of Optimization Algorithms: A Comparison between Data-Driven Normalization and Scaling Factor-Based Methods Using PEPSSBI
- Dynamic Optimization Approach to Estimate Kinetic Parameters of Monod-Based Microalgae Growth Models
- Automatic Assembly and Calibration of Models of Enzymatic Reactions Based on Ordinary Differential Equations
- Data Processing to Probe the Cellular Hydrogen Peroxide Landscape
- Computational Methods for Structure-Based Drug Design through Systems Biology
- Model Setup and Procedures for Prediction of Enzyme Reaction Kinetics with QM-Only and QM:MM Approaches
- The Role of Ligand Rebinding and Facilitated Dissociation on the Characterization of Dissociation Rates by Surface Plasmon Resonance (SPR) and Benchmarking Performance Metrics
- Computational Tools for Accurate Binding Free Energy Prediction
- Computational Alanine Scanning Reveals Common Features of TCR/pMHC Recognition in HLA-DQ8-Associated Celiac Disease
- Umbrella Sampling-Based Method to Compute Ligand-Binding Affinity
- Creating Maps of the Ligand Binding Landscape for Kinetics-Based Drug Discovery
- Prediction of Protein–Protein Binding Affinities from Unbound Protein Structures
- Parameter Optimization for Ion Channel Models: Integrating New Data with Known Channel Properties.